/usr/lib/python2.7/dist-packages/taskflow/engines/action_engine/builder.py is in python-taskflow 2.3.0-2.
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# Copyright (C) 2012 Yahoo! Inc. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License"); you may
# not use this file except in compliance with the License. You may obtain
# a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS, WITHOUT
# WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the
# License for the specific language governing permissions and limitations
# under the License.
from concurrent import futures
import weakref
from automaton import machines
from oslo_utils import timeutils
from taskflow import logging
from taskflow import states as st
from taskflow.types import failure
from taskflow.utils import iter_utils
# Default waiting state timeout (in seconds).
WAITING_TIMEOUT = 60
# Meta states the state machine uses.
UNDEFINED = 'UNDEFINED'
GAME_OVER = 'GAME_OVER'
META_STATES = (GAME_OVER, UNDEFINED)
# Event name constants the state machine uses.
SCHEDULE = 'schedule_next'
WAIT = 'wait_finished'
ANALYZE = 'examine_finished'
FINISH = 'completed'
FAILED = 'failed'
SUSPENDED = 'suspended'
SUCCESS = 'success'
REVERTED = 'reverted'
START = 'start'
# Internal enums used to denote how/if a atom was completed."""
FAILED_COMPLETING = 'failed_completing'
WAS_CANCELLED = 'was_cancelled'
SUCCESSFULLY_COMPLETED = 'successfully_completed'
# For these states we will gather how long (in seconds) the
# state was in-progress (cumulatively if the state is entered multiple
# times)
TIMED_STATES = (st.ANALYZING, st.RESUMING, st.SCHEDULING, st.WAITING)
LOG = logging.getLogger(__name__)
class MachineMemory(object):
"""State machine memory."""
def __init__(self):
self.next_up = set()
self.not_done = set()
self.failures = []
self.done = set()
def cancel_futures(self):
"""Attempts to cancel any not done futures."""
for fut in self.not_done:
fut.cancel()
class MachineBuilder(object):
"""State machine *builder* that powers the engine components.
NOTE(harlowja): the machine (states and events that will trigger
transitions) that this builds is represented by the following
table::
+--------------+------------------+------------+----------+---------+
| Start | Event | End | On Enter | On Exit |
+--------------+------------------+------------+----------+---------+
| ANALYZING | completed | GAME_OVER | . | . |
| ANALYZING | schedule_next | SCHEDULING | . | . |
| ANALYZING | wait_finished | WAITING | . | . |
| FAILURE[$] | . | . | . | . |
| GAME_OVER | failed | FAILURE | . | . |
| GAME_OVER | reverted | REVERTED | . | . |
| GAME_OVER | success | SUCCESS | . | . |
| GAME_OVER | suspended | SUSPENDED | . | . |
| RESUMING | schedule_next | SCHEDULING | . | . |
| REVERTED[$] | . | . | . | . |
| SCHEDULING | wait_finished | WAITING | . | . |
| SUCCESS[$] | . | . | . | . |
| SUSPENDED[$] | . | . | . | . |
| UNDEFINED[^] | start | RESUMING | . | . |
| WAITING | examine_finished | ANALYZING | . | . |
+--------------+------------------+------------+----------+---------+
Between any of these yielded states (minus ``GAME_OVER`` and ``UNDEFINED``)
if the engine has been suspended or the engine has failed (due to a
non-resolveable task failure or scheduling failure) the machine will stop
executing new tasks (currently running tasks will be allowed to complete)
and this machines run loop will be broken.
NOTE(harlowja): If the runtimes scheduler component is able to schedule
tasks in parallel, this enables parallel running and/or reversion.
"""
def __init__(self, runtime, waiter):
self._runtime = weakref.proxy(runtime)
self._analyzer = runtime.analyzer
self._completer = runtime.completer
self._scheduler = runtime.scheduler
self._storage = runtime.storage
self._waiter = waiter
def build(self, statistics, timeout=None, gather_statistics=True):
"""Builds a state-machine (that is used during running)."""
if gather_statistics:
watches = {}
state_statistics = {}
statistics['seconds_per_state'] = state_statistics
watches = {}
for timed_state in TIMED_STATES:
state_statistics[timed_state.lower()] = 0.0
watches[timed_state] = timeutils.StopWatch()
statistics['discarded_failures'] = 0
statistics['awaiting'] = 0
statistics['completed'] = 0
statistics['incomplete'] = 0
memory = MachineMemory()
if timeout is None:
timeout = WAITING_TIMEOUT
# Cache some local functions/methods...
do_complete = self._completer.complete
do_complete_failure = self._completer.complete_failure
get_atom_intention = self._storage.get_atom_intention
def do_schedule(next_nodes):
return self._scheduler.schedule(
sorted(next_nodes,
key=lambda node: getattr(node, 'priority', 0),
reverse=True))
def iter_next_atoms(atom=None, apply_deciders=True):
# Yields and filters and tweaks the next atoms to run...
maybe_atoms_it = self._analyzer.iter_next_atoms(atom=atom)
for atom, late_decider in maybe_atoms_it:
if apply_deciders:
proceed = late_decider.check_and_affect(self._runtime)
if proceed:
yield atom
else:
yield atom
def resume(old_state, new_state, event):
# This reaction function just updates the state machines memory
# to include any nodes that need to be executed (from a previous
# attempt, which may be empty if never ran before) and any nodes
# that are now ready to be ran.
memory.next_up.update(
iter_utils.unique_seen((self._completer.resume(),
iter_next_atoms())))
return SCHEDULE
def game_over(old_state, new_state, event):
# This reaction function is mainly a intermediary delegation
# function that analyzes the current memory and transitions to
# the appropriate handler that will deal with the memory values,
# it is *always* called before the final state is entered.
if memory.failures:
return FAILED
leftover_atoms = iter_utils.count(
# Avoid activating the deciders, since at this point
# the engine is finishing and there will be no more further
# work done anyway...
iter_next_atoms(apply_deciders=False))
if leftover_atoms:
# Ok we didn't finish (either reverting or executing...) so
# that means we must of been stopped at some point...
LOG.trace("Suspension determined to have been reacted to"
" since (at least) %s atoms have been left in an"
" unfinished state", leftover_atoms)
return SUSPENDED
elif self._analyzer.is_success():
return SUCCESS
else:
return REVERTED
def schedule(old_state, new_state, event):
# This reaction function starts to schedule the memory's next
# nodes (iff the engine is still runnable, which it may not be
# if the user of this engine has requested the engine/storage
# that holds this information to stop or suspend); handles failures
# that occur during this process safely...
current_flow_state = self._storage.get_flow_state()
if current_flow_state == st.RUNNING and memory.next_up:
not_done, failures = do_schedule(memory.next_up)
if not_done:
memory.not_done.update(not_done)
if failures:
memory.failures.extend(failures)
memory.next_up.intersection_update(not_done)
elif current_flow_state == st.SUSPENDING and memory.not_done:
# Try to force anything not cancelled to now be cancelled
# so that the executor that gets it does not continue to
# try to work on it (if the future execution is still in
# its backlog, if it's already being executed, this will
# do nothing).
memory.cancel_futures()
return WAIT
def complete_an_atom(fut):
# This completes a single atom saving its result in
# storage and preparing whatever predecessors or successors will
# now be ready to execute (or revert or retry...); it also
# handles failures that occur during this process safely...
atom = fut.atom
try:
outcome, result = fut.result()
do_complete(atom, outcome, result)
if isinstance(result, failure.Failure):
retain = do_complete_failure(atom, outcome, result)
if retain:
memory.failures.append(result)
else:
# NOTE(harlowja): avoid making any intention request
# to storage unless we are sure we are in DEBUG
# enabled logging (otherwise we will call this all
# the time even when DEBUG is not enabled, which
# would suck...)
if LOG.isEnabledFor(logging.DEBUG):
intention = get_atom_intention(atom.name)
LOG.debug("Discarding failure '%s' (in response"
" to outcome '%s') under completion"
" units request during completion of"
" atom '%s' (intention is to %s)",
result, outcome, atom, intention)
if gather_statistics:
statistics['discarded_failures'] += 1
if gather_statistics:
statistics['completed'] += 1
except futures.CancelledError:
# Well it got cancelled, skip doing anything
# and move on; at a further time it will be resumed
# and something should be done with it to get it
# going again.
return WAS_CANCELLED
except Exception:
memory.failures.append(failure.Failure())
LOG.exception("Engine '%s' atom post-completion"
" failed", atom)
return FAILED_COMPLETING
else:
return SUCCESSFULLY_COMPLETED
def wait(old_state, new_state, event):
# TODO(harlowja): maybe we should start doing 'yield from' this
# call sometime in the future, or equivalent that will work in
# py2 and py3.
if memory.not_done:
done, not_done = self._waiter(memory.not_done, timeout=timeout)
memory.done.update(done)
memory.not_done = not_done
return ANALYZE
def analyze(old_state, new_state, event):
# This reaction function is responsible for analyzing all nodes
# that have finished executing/reverting and figuring
# out what nodes are now ready to be ran (and then triggering those
# nodes to be scheduled in the future); handles failures that
# occur during this process safely...
next_up = set()
while memory.done:
fut = memory.done.pop()
# Force it to be completed so that we can ensure that
# before we iterate over any successors or predecessors
# that we know it has been completed and saved and so on...
completion_status = complete_an_atom(fut)
if (not memory.failures
and completion_status != WAS_CANCELLED):
atom = fut.atom
try:
more_work = set(iter_next_atoms(atom=atom))
except Exception:
memory.failures.append(failure.Failure())
LOG.exception("Engine '%s' atom post-completion"
" next atom searching failed", atom)
else:
next_up.update(more_work)
current_flow_state = self._storage.get_flow_state()
if (current_flow_state == st.RUNNING
and next_up and not memory.failures):
memory.next_up.update(next_up)
return SCHEDULE
elif memory.not_done:
if current_flow_state == st.SUSPENDING:
memory.cancel_futures()
return WAIT
else:
return FINISH
def on_exit(old_state, event):
LOG.trace("Exiting old state '%s' in response to event '%s'",
old_state, event)
if gather_statistics:
if old_state in watches:
w = watches[old_state]
w.stop()
state_statistics[old_state.lower()] += w.elapsed()
if old_state in (st.SCHEDULING, st.WAITING):
statistics['incomplete'] = len(memory.not_done)
if old_state in (st.ANALYZING, st.SCHEDULING):
statistics['awaiting'] = len(memory.next_up)
def on_enter(new_state, event):
LOG.trace("Entering new state '%s' in response to event '%s'",
new_state, event)
if gather_statistics and new_state in watches:
watches[new_state].restart()
state_kwargs = {
'on_exit': on_exit,
'on_enter': on_enter,
}
m = machines.FiniteMachine()
m.add_state(GAME_OVER, **state_kwargs)
m.add_state(UNDEFINED, **state_kwargs)
m.add_state(st.ANALYZING, **state_kwargs)
m.add_state(st.RESUMING, **state_kwargs)
m.add_state(st.REVERTED, terminal=True, **state_kwargs)
m.add_state(st.SCHEDULING, **state_kwargs)
m.add_state(st.SUCCESS, terminal=True, **state_kwargs)
m.add_state(st.SUSPENDED, terminal=True, **state_kwargs)
m.add_state(st.WAITING, **state_kwargs)
m.add_state(st.FAILURE, terminal=True, **state_kwargs)
m.default_start_state = UNDEFINED
m.add_transition(GAME_OVER, st.REVERTED, REVERTED)
m.add_transition(GAME_OVER, st.SUCCESS, SUCCESS)
m.add_transition(GAME_OVER, st.SUSPENDED, SUSPENDED)
m.add_transition(GAME_OVER, st.FAILURE, FAILED)
m.add_transition(UNDEFINED, st.RESUMING, START)
m.add_transition(st.ANALYZING, GAME_OVER, FINISH)
m.add_transition(st.ANALYZING, st.SCHEDULING, SCHEDULE)
m.add_transition(st.ANALYZING, st.WAITING, WAIT)
m.add_transition(st.RESUMING, st.SCHEDULING, SCHEDULE)
m.add_transition(st.SCHEDULING, st.WAITING, WAIT)
m.add_transition(st.WAITING, st.ANALYZING, ANALYZE)
m.add_reaction(GAME_OVER, FINISH, game_over)
m.add_reaction(st.ANALYZING, ANALYZE, analyze)
m.add_reaction(st.RESUMING, START, resume)
m.add_reaction(st.SCHEDULING, SCHEDULE, schedule)
m.add_reaction(st.WAITING, WAIT, wait)
m.freeze()
return (m, memory)
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